A number of software-based systems are known in the art for the monitoring and analysis of VoIP networks. These include, by way of example, Chariot™ VoIP Assessor Version 1.0, commercially available from NetIQ Corporation of San Jose, Calif., and NetAlly™ VoIP, commercially available from Viola Networks of Somerset, N.J., formerly Omegon Ltd. Such systems typically monitor and analyze network-level VoIP performance in terms of quality of service (QoS) or compliance with service level agreements (SLAs), using packet-based measurements such as jitter, loss and delay.
Known systems of the type described above generally make use of so-called “synthetic” IP telephones, as opposed to actual IP telephones. A synthetic IP telephone is a software agent that generates VoIP call traffic. Unfortunately, there are a number of significant disadvantages associated with the use of synthetic IP telephones in a VoIP monitoring and analysis system. For example, a given synthetic IP telephone may require a separate installation of computer hardware and software proximate to one or more actual IP telephones and programmed to predict the QoS of the actual IP telephones. In addition, synthetic IP phones merely simulate hardware and software elements of an actual IP telephone, such as network interfaces, codecs, and jitter buffers, and as a result can introduce errors into the system. Synthetic IP telephones are generally configured to run on general-purpose computing platforms, such as personal computers (PCs), and are generally not designed to run on a telephony platform such as a private branch exchange (PBX), enterprise switch or other communication system switch.
Another significant problem with conventional monitoring and analysis systems is that they are often configured such that application-related effects can lead to mischaracterization of the actual contribution of the network to a given measurement. For example, the actual transmit time for sending out test traffic over the network in the conventional systems may be significantly delayed relative to its recorded transmit time if the device on which the synthetic IP telephone is implemented becomes busy with other processing tasks, thereby rendering the resulting measurements inaccurate.
Yet another problem relates to clock synchronization. Conventional techniques typically utilize a clock synchronization approach, in which the system attempts to synchronize the clocks of the devices on which the synthetic IP telephones are implemented, prior to taking any measurements involving those devices. Unfortunately, this approach is problematic in that clock synchronization takes an excessive amount of time, and thus unduly limits the responsiveness of the system to changing network conditions. Moreover, clock synchronization can fail altogether, since it depends on network conditions at the time the synchronization process is carried out, and these conditions may be unfavorable to accurate synchronization. Poor network conditions in a given segment of the network can preclude accurate synchronization of the associated devices, and as a result the system may be unable to analyze this network segment.
Other known network monitoring and analysis systems utilize a so-called “passive” approach which involves monitoring actual random call traffic over the network. This approach has very limited flexibility, in that it relies on actual call traffic generated by actual users rather than targeted traffic generated in accordance with specified test parameters.
As is apparent from the foregoing, conventional systems suffer from a number of significant problems, and may fail to provide optimal accuracy for measures such as jitter, loss and delay. A need therefore exists for improved techniques for monitoring and analysis of VoIP communications and other types of traffic in network-based systems.